344
---
title: "Dashboarding Demo"
output:
flexdashboard::flex_dashboard:
orientation: row #another option is columns
vertical_layout: fill
social: ["menu"] #to have links to social media
source_code: embed #link to get source code
theme:
version: 4
bootswatch: spacelab #see bootswatch.com site for other themes
---
```{r, include=FALSE}
# RStudio 2021.09.0+351 "Ghost Orchid" Release
# (077589bcad3467ae79f318afe8641a1899a51606, 2021-09-20) for Windows
# Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)
# QtWebEngine/5.12.8 Chrome/69.0.3497.128 Safari/537.36
```
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(palmerpenguins)
library(plotly)
library(DT)
library(fontawesome)
#load data from palmerpenguins
data("penguins")
head(penguins)
```
plots {data-navmenu="Pages"}
======================================================================
Sidebar {.sidebar}
-------------------------------------------------------------------
### Penguin Stats
The number of penguins in the data is `r nrow(penguins)`
Row
-------------------------------------------------------------------
### Number of penguins
```{r}
valueBox(nrow(penguins), icon = "fa-linux") #font awesome icon
```
### Avg body mass
```{r}
avg_mass = round(mean(penguins$body_mass_g, na.rm = T), 1)
gauge(avg_mass,
min(0),
max = max(penguins$body_mass_g, na.rm = T),
gaugeSectors(success = c(4000, 6300),
warning = c(2000, 3999),
danger = c(0, 1999)))
```
Column {.tabset}
-----------------------------------------------------------------------
### Scatter plot of bill length vs bill depth
```{r}
a = penguins %>% ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species))+
geom_point()
ggplotly(a)
#htmlwidgets.org & Showcase for more html options; try leaflet (interactive maps)
# -also check the Gallery for registered widgets to try
```
### Chart B
```{r}
penguins %>% ggplot(aes(x = body_mass_g, y = sex, fill = sex))+
geom_boxplot()
```
### Chart C
```{r}
penguins %>% ggplot(aes(x = flipper_length_mm, fill = species))+
geom_histogram()+
facet_wrap(~species)
```
data {data-navmenu="Pages"}
=========================================================================
```{r}
penguins %>% datatable(extensions = "Buttons",
options = list(dom = "Blfrtip",
buttons = c("copy", "csv", "excel",
"pdf", "print")))
#B for Buttons, l for length, t for table, p for pagination, f for _, r for _, i for _
# lfrtip is the default
#Go to datatables.net to see all options to customize html table
```